{"url":"/dataset/opt","name":"OPT","full_name":"Object Pose Tracking","description_markdown":"Accurately tracking the six degree-of-freedom pose of an object in real scenes is an important task in computer vision and augmented reality with numerous applications. Although a variety of algorithms for this task have been proposed, it remains difficult to evaluate existing methods in the literature as oftentimes different sequences are used and no large benchmark datasets close to real-world scenarios are available. In this paper, we present a large object pose tracking benchmark dataset consisting of RGB-D video sequences of 2D and 3D targets with ground-truth information. The videos are recorded under various lighting conditions, different motion patterns and speeds with the help of a programmable robotic arm. We present extensive quantitative evaluation results of the state-of-the-art methods on this benchmark dataset and discuss the potential research directions in this field.","description_withheld":null,"homepage":"http://media.ee.ntu.edu.tw/research/OPT/","introduced_date":"2017-10-30","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"6D Pose Estimation","url":"/task/6d-pose-estimation-1","datasets_with_task":"/datasets/task/6d-pose-estimation-1"}],"languages":[],"variants":["OPT"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/6d-pose-estimation-on-opt","task":"6D Pose Estimation","dataset_variant":"OPT","rows":2,"metrics":["AUC"],"first_row_in_archive_order":{"model":"ICG+","paper":"/paper/fusing-visual-appearance-and-geometry-for","metrics":{"AUC":"17.57"},"code_links":[{"title":"dlr-rm/3dobjecttracking","url":"https://github.com/dlr-rm/3dobjecttracking"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/fusing-visual-appearance-and-geometry-for","title":"Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking","date":"2023-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/iterative-corresponding-geometry-fusing","title":"Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects","date":"2022-03-10","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}